Category: AWS re:Invent

Today, Amazon Inspector adds three new capabilities to increase the realm of possibilities when scanning your workloads for software vulnerabilities: Amazon Inspector introduces a new set of open source plugins and an API allowing you to assess your container images for software vulnerabilities at build time directly from your continuous integration and continuous delivery (CI/CD) […]

One of the challenges with distributed systems is that they are made up of many interdependent services, which add a degree of complexity when you are trying to monitor their performance. Determining which services and APIs are experiencing high latencies or degraded availability requires manually putting together telemetry signals. This can result in time and […]

Today, we are announcing the general availability of myApplications supporting application operations, a new set of capabilities that help you get started with your applications on AWS, operate them with less effort, and move faster at scale. With myApplications in the AWS Management Console, you can more easily manage and monitor the cost, health, security […]

Today we are excited to announce the general availability of SaaS Quick Launch, a new feature in AWS Marketplace that makes it easy and secure to deploy SaaS products. Before SaaS Quick Launch, configuring and launching third-party SaaS products could be time-consuming and costly, especially in certain categories like security and monitoring. Some products require […]

I’m happy to share that Amazon SageMaker now comes with an improved model deployment experience to help you deploy traditional machine learning (ML) models and foundation models (FMs) faster. As a data scientist or ML practitioner, you can now use the new ModelBuilder class in the SageMaker Python SDK to package models, perform local inference […]

Today, I’m happy to introduce the ability to use natural language instructions in Amazon SageMaker Canvas to explore, visualize, and transform data for machine learning (ML). SageMaker Canvas now supports using foundation model-(FM) powered natural language instructions to complement its comprehensive data preparation capabilities for data exploration, analysis, visualization, and transformation. Using natural language instructions, […]

Today, we are announcing new Amazon SageMaker inference capabilities that can help you optimize deployment costs and reduce latency. With the new inference capabilities, you can deploy one or more foundation models (FMs) on the same SageMaker endpoint and control how many accelerators and how much memory is reserved for each FM. This helps to […]

Today, I’m excited to introduce a new capability in Amazon SageMaker Canvas to use foundation models (FMs) from Amazon Bedrock and Amazon SageMaker Jumpstart through a no-code experience. This new capability makes it easier for you to evaluate and generate responses from FMs for your specific use case with high accuracy. Every business has its […]